Parameterised time-frequency analysis methods and their engineering applications: A review of recent advances
It is well known that time-frequency analysis (TFA) characterises signals in time-frequency
plane. Theoretically, traditional non-parameterised TFA can analyze any signal, but it is …
plane. Theoretically, traditional non-parameterised TFA can analyze any signal, but it is …
Review of geoacoustic inversion in underwater acoustics
NR Chapman, EC Shang - Journal of Theoretical and …, 2021 - World Scientific
This paper reviews the progress in geoacoustic inversion over the past several decades.
The review is separated into two parts. The first part reviews developments in model-based …
The review is separated into two parts. The first part reviews developments in model-based …
Nonlinear time-warping made simple: A step-by-step tutorial on underwater acoustic modal separation with a single hydrophone
Classical ocean acoustic experiments involve the use of synchronized arrays of sensors.
However, the need to cover large areas and/or the use of small robotic platforms has evoked …
However, the need to cover large areas and/or the use of small robotic platforms has evoked …
Bayesian geoacoustic inversion of single hydrophone light bulb data using warping dispersion analysis
This paper presents geoacoustic inversion of a light bulb implosion recorded during the
Shallow Water 2006 experiment. The source is low frequency and impulsive, the …
Shallow Water 2006 experiment. The source is low frequency and impulsive, the …
Matched-field geoacoustic inversion based on radial basis function neural network
Y Shen, X Pan, Z Zheng, P Gerstoft - The Journal of the Acoustical …, 2020 - pubs.aip.org
Multi-layer neural networks (NNs) are combined with objective functions of matched-field
inversion (MFI) to estimate geoacoustic parameters. By adding hidden layers, a radial basis …
inversion (MFI) to estimate geoacoustic parameters. By adding hidden layers, a radial basis …
Block sparse Bayesian learning for broadband mode extraction in shallow water from a vertical array
The horizontal wavenumbers and modal depth functions are estimated by block sparse
Bayesian learning (BSBL) for broadband signals received by a vertical line array in shallow …
Bayesian learning (BSBL) for broadband signals received by a vertical line array in shallow …
Single-receiver geoacoustic inversion using modal reversal
This paper introduces a single-receiver geoacoustic-inversion method based on dispersion
analysis and adapted to low-frequency impulsive sources in shallow-water environments. In …
analysis and adapted to low-frequency impulsive sources in shallow-water environments. In …
Deep-learning geoacoustic inversion using multi-range vertical array data in shallow water
A multi-range vertical array data processing (MRP) method based on a convolutional neural
network (CNN) is proposed to estimate geoacoustic parameters in shallow water. The …
network (CNN) is proposed to estimate geoacoustic parameters in shallow water. The …
Characterizing the seabed in the Straits of Florida by using acoustic noise interferometry and time warping
Interferometry of ambient and shipping noise in the ocean provides a way to estimate
physical parameters of the seafloor and the water column in an environmentally friendly …
physical parameters of the seafloor and the water column in an environmentally friendly …
Hybrid seabed parameterization to investigate geoacoustic gradients at the New England Mud Patch
This article applies Bayesian geoacoustic inversion with a hybrid seabed-model
parameterization to modal-dispersion data from the New England Mud Patch to estimate …
parameterization to modal-dispersion data from the New England Mud Patch to estimate …